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MATH 261 - Scientific Computing |

Scientific computing describes a broad array of techniques and ideas used to implement mathematical and statistical algorithms on a computer. In this class, we will focus on the application of computing to data analysis. We will explore theory and algorithms that underlie regression, classification, clustering, and dimension reduction. A particular emphasis will be placed on numerical optimization, one of the main pillars of scientific computing. As the course progresses, we will find that implementation of many algorithms will depend on numerically solving, that is on a computer, some basic problems from linear algebra and calculus, leading us to cover some key ideas in numerical analysis and numerical linear algebra. Programming in R will be an essential component of the course, although no previous programming experience is needed. 3.000 Credit hours 3.000 Lecture hours Levels: Undergraduate Schedule Types: Lecture, Seminar Mathematics Department Course Attributes: Mean Grade is Calculated Prerequisites: MATH 137 and MATH 150 |

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